Overview
COURSE DESCRIPTION
Deep learning is a subfield of machine learning that has revolutionized many industries, including computer vision, natural language processing, and speech recognition. It is powered by artificial neural networks, complex mathematical models that can learn from data to perform complex tasks.
TensorFlow is an open-source software library for building and training deep learning models. It is one of the most popular deep-learning libraries used by researchers and practitioners alike to build state-of-the-art models.
In this course, you will learn how to use TensorFlow to build and train deep-learning models for various tasks. You will start with the basics of TensorFlow, including tensors, operations, and neural networks. Then, you will learn how to build and train models for different tasks, such as image classification, object detection, and natural language processing.
The course is designed for students with a basic understanding of Python and machine learning. No prior experience with TensorFlow is required.
PREREQUISITE
This course is designed for students with a basic understanding of Python and machine learning. No prior experience with TensorFlow is required.
Course Materials
COURSE MATERIALS
Video lectures
Jupyter notebooks
Code examples
Exercises and assignments
Course Features
- Lectures 38
- Quiz 0
- Duration 33 hours
- Skill level Beginner
- Language English
- Students 100
- Assessments Yes
Curriculum
Curriculum
- 9 Sections
- 38 Lessons
- 45 Hours
- Introduction to Deep Learning5
- TensorFlow Fundamentals5
- Building Deep Learning Models with TensorFlow5
- Advanced Deep Learning Techniques5
- Deep Learning for Natural Language Processing (NLP)5
- Deep Learning for Computer Vision (CV)4
- Deep Learning for Other Applications4
- Deep Learning Best Practices4
- Course Projects1